Research on LSTM-A2C Intelligent Futures Pairs Trading Model Integrating Price Spread Features
Sun, Zhai and He (2026) study pairs trading and statistical arbitrage across several asset classes using a recurrent neural network over 2019–2024. The abstract mentions a Sharpe ratio, excess returns, profits and an out-of-sample test but not a benchmark, transaction costs, multiple testing or the size of the universe.
“Finally, an RL module based on the Advantage Actor-Critic (A2C) algorithm incorporates spread predictions into the state space and employs a diversified reward function to learn optimal trading strategies.”
AssetMulti-assetfutures
StrategyPairs trading
TechniqueRecurrent neural networkfeedforward network
GeographyChina
Also stated: Daily, 2019–2024, Sharpe ratio, Excess return, Profit, Long-short, Price and volume, out-of-sample test
Missing from abstract: benchmark, costs, multiple testing, universe
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The paper's neighbourhoodPairs trading and statistical arbitrage by year
FamilyPairs trading and statistical arbitrage93Momentum and trend following289Factor investing240Machine learning return prediction15318 more · 909
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
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